With business exploring the digital landscape more than ever now, AI is all set to add greater value to business digitalization. The difficult time is heralding a new normal for every industry, especially the manufacturing industry. To make production a seamless and efficient process, manufacturers are exploring opportunities with the digital twin technology. Advocates of simulated virtual reality believe that AI and digital twin technologies are the future of the digital landscape for businesses.
In this article, we will explore how AI development services complement digital twin and IoT technologies to build innovative, efficient, and revenue-generating outputs.
Global industries are designed with heavy assets, complex production lines, and prodigious amounts of domain-specific data. Most of the data and their calculations are not available for crucial decisions which means it takes lots of time, effort, costs, and many more things.
The Digital Twin technology is used for visualizing the flow of materials through a process in real-time. The technology enables manufacturers to represent the physical aspect of material and equipment on a digital screen with the help of virtually-simulated images and visuals. The technology is a great way to reduce most of the efforts, costs, and time required for monitoring the process flow at production units. It will help to improve business growth. It's becoming frequently popular with the growth of advanced technology. It fills the gap between the physical and the virtual environment.
The combination of digital twin and machine learning development is emerging as a powerful duo to bring significant automation to the production and assembly processes. Under ML, location and mapping algorithms empower Automated Guided Vehicles (AGVs) with-
1. Automotive Industry - Digital Twin Technology is used in the Automotive Industry during development, testing, and validation of autonomous vehicles. The most popular example of the Automotive Industry is automatic vehicles that are able to test the senses of the traffic and environment.
2. Asset Performace - The use case of AI and digital twin technology in monitoring asset performance involves a granular analysis of the machine condition in real-time. The duo enables analysts to overlay real-life equipment with performance data to identify any shortcomings.
3. 3D Modelling - In 3D Models, Digital Twin Technology helps to capture the data while the physical asset performs and store it.
4. HealthCare - Digital Twin Technology most popular in Health Industry due to its techniques which helps to find the patient's and machine's health records, which performs under different circumstances. It analyzes the record of patience and machines and indicates what kind of disease she/he have.
5. Wind Turbines - Digital Twin Technology use in The energy sector as well. It helps to monitor the energy generation and utilization of capacity across verticals. Wind turbine digital twins can help integrate energy data and assess growth and gaps to be filled.
Through AI in Digital Twin Technology, businesses can build a model that observes the behavior of assets and capture the images while in action and use the data and images in a unique way. This information on assets helps AI to make complex decisions and reduce the developer's time and costs.